Background: For the functional control of prosthetic hand, it is insufficient to obtain\nonly the motion pattern information. As far as practicality is concerned, the control of\nthe prosthetic hand force is indispensable. The application value of prosthetic hand will\nbe greatly improved if the stable grip of prosthetic hand can be achieved. To address\nthis problem, in this study, a bio-signal control method for grasping control of a prosthetic\nhand is proposed to improve patientâ??s sense of using prosthetic hand and the\nthus improving the quality of life.\nMethods: A MYO gesture control armband is used to collect the surface electromyographic\n(sEMG) signals from the upper limb. The overlapping sliding window scheme\nare applied for data segmentation and the correlated features are extracted from each\nsegmented data. Principal component analysis (PCA) methods are then deployed for\ndimension reduction. Deep neural network is used to generate sEMG-force regression\nmodel for force prediction at different levels. The predicted force values are input to\na fuzzy controller for the grasping control of a prosthetic hand. A vibration feedback\ndevice is used to feed grasping force value back to patientâ??s arm to improve patientâ??s\nsense of using prosthetic hand and realize accurate grasping. To test the effectiveness\nof the scheme, 15 able-bodied subjects participated in the experiments.\nResults: The classification results indicated that 8-channel sEMG applying all four\ntime-domain features, with PCA reduction from 32 to 8 dimensions results in the highest\nclassification accuracy. Based on the experimental results from 15 participants, the\naverage recognition rate is over 95%. On the other hand, from the statistical results of\nstandard deviation, the between-subject variations ranges from 3.58 to 1.25%, proving\nthat the robustness and stability of the proposed approach.\nConclusions: The method proposed hereto control grasping power through the\npatientâ??s own sEMG signal, which achieves a high recognition rate to improve the\nsuccess rate of grip and increases the sense of operation and also brings the gospel for\nupper extremity amputation patients.
Loading....